In epidemiology incidence denotes the rate of occurrence of new cases (of disease), while prevalence is the frequency in the population (of diseased people). From a statistical point of view it is useful to understand incidence and prevalence in the parameter space, incidence as intensity (hazard) and prevalence as probability, and to relate observable quantities to these via a statistical model. In this paper such a framework is based on modelling each individual's dynamics in the Lexis diagram by a simple three-state stochastic process in the age direction and recruiting individuals from a Poisson process in the time direction. The resulting distributions in the cross-sectional population allow a rigorous discussion of the interplay between age-specific incidence and prevalence as well as of the statistical analysis of epidemiological cross-sectional data. For the latter, this paper focuses on methods from modern nonparametric continuous time survival analysis, including random censoring and truncation models and estimation under monotonicity constraints. The exposition is illustrated by examples, primarily from the author's epidemiological experience.
Originally called the Journal of the Statistical Society of London when founded in 1838 and renamed the Journal of the Royal Statistical Society when the Society was granted its Royal Charter in 1887, what is now known as Series A of the journal (Statistics in Society) is essentially a journal of general statistical interest. It publishes papers whose appeal lies in their subject-matter rather than their technical statistical content. Medical, social, educational, legal, demographic and governmental issues are of particular concern. The journal encourages serious statistical thinking on issues of importance to society, especially on substantive matters aimed at taking debate outside the confines of the statistical profession. JSTOR provides a digital archive of the print version of Journal of the Royal Statistical Society, Series A: Statistics in Society. The electronic version of Journal of the Royal Statistical Society, Series A: Statistics in Society is available at http://www.interscience.wiley.com. Authorized users may be able to access the full text articles at this site.
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Journal of the Royal Statistical Society. Series A (Statistics in Society)
© 1991 Royal Statistical Society
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